A power amplifier for amplifying a transmitted signal is used in a radio transmitter which transmits a radio signal in a radio communication system. A power amplifier has a linear characteristic in a region in which the amplitude of an input signal is small. That is to say, there is an approximately linear relationship between the amplitude of an input signal and the amplitude of an output signal. On the other hand, a power amplifier has a nonlinear characteristic in a region in which the amplitude of an input signal is large. That is to say, there is a nonlinear relationship between the amplitude of an input signal and the amplitude of an output signal. In many cases, a power amplifier is made to operate not only in the linear region but also in the nonlinear region in order to efficiently utilize a power amplifier.
For example, however, nonlinear distortion of a transmitted signal due to the nonlinear amplification characteristic of a power amplifier may cause power leakage from a desired frequency band to an adjacent frequency band. As a result, radio communication quality deteriorates. Accordingly, a radio transmitter may perform predistortion-type distortion compensation as one of methods for linearizing the nonlinear amplification characteristic of a power amplifier. With the predistortion-type distortion compensation a radio transmitter includes a predistorter as a linearizer.
The predistorter gives an input signal inputted to a power amplifier nonlinear distortion reverse to the nonlinear characteristic of the power amplifier. For example, the predistorter gives each input signal gain according to its level. By passing an input signal to which nonlinear distortion reverse to the nonlinear characteristic of the power amplifier is given through the power amplifier, nonlinear distortion of an amplified transmitted signal is controlled. However, it is not easy to correctly estimate in advance a characteristic reverse to the nonlinear characteristic of a power amplifier. Therefore, the method of learning (updating) a compensation coefficient used by a predistorter while operating a power amplifier may be adopted.
A polynomial method or a LUT (Lookup Table) method is proposed as a method implemented in a predistorter. With the polynomial method a characteristic reverse to the nonlinear characteristic of a power amplifier is represented as a polynomial including a variable indicative of the level of an input signal and a plurality of coefficients. With the LUT method a characteristic reverse to the nonlinear characteristic of a power amplifier is represented as a table in which the level of an input signal is associated with gain given thereto.
A direct learning method, an indirect learning method, or a model inversion method is proposed as a method for learning a compensation coefficient to be used by a predistorter. With the direct learning method, a comparison is made between a feedback signal from a power amplifier and an input signal before distortion compensation and a compensation coefficient is updated so that an error between them will become smaller. With the indirect learning method, a training distorter for applying a compensation coefficient to a feedback signal from a power amplifier is used and the compensation coefficient is updated so that an error between an input signal after distortion compensation and an output from the training distorter will become smaller. A compensation coefficient learned by the training distorter is copied to a predistorter. With the model inversion method, a modeler for applying a model of a power amplifier to an input signal after distortion compensation is used and the model is updated so that an error between a feedback signal from the power amplifier and an output from the modeler will become smaller. A compensation coefficient indicative of a characteristic (inverse model) reverse to the nonlinear characteristic of a model learned by the modeler is then calculated and is set in a predistorter.
By the way, various signal processing units, such as an ADC (Analog to Digital Converter), may be used on a feedback path along which a feedback signal is obtained from a power amplifier. A great bandwidth of a feedback signal which passes along the feedback path may have disadvantages. For example, a load at the time of compensation coefficient learning is heavy or the costs are high because of the use of high performance signal processing units. Accordingly, a linearizer including an LPF (Low Pass Filter) on a feedback path is proposed. This linearizer removes high-frequency components by the use of the LPF. By doing so, the linearizer limits a bandwidth of a feedback signal, compared with a transmitted signal outputted from a power amplifier. As a result, the linearizer learns a compensation coefficient indicative of a characteristic reverse to the nonlinear characteristic of the power amplifier on the basis of the feedback signal whose bandwidth is limited.
Japanese Laid-open Patent Publication No. 2013-106330
Hsin-Hung Chen, Chih-Hung Lin, Po-Chiun Huang and Tsair Chen, “Joint Polynomial and Look-Up-Table Predistortion Power Amplifier Linearization”, IEEE (Institute of Electrical and Electronics Engineers) Transactions on Circuits and Systems-II: Express Briefs, Vol. 53 No. 8, pp. 612-616, August 2006
Yuelin Ma, Songbai He, Yoshihiko Akaiwa and Yasushi Yamamoto, “An Open-Loop Digital Predistortor Based on Memory Polynomial Inverses for Linearization of RF Power Amplifier”, International Journal of RF and Microwave Computer-Aided Engineering, Vol. 21 No. 5, pp. 589-595, September 2011
As stated above, the learning method of learning a compensation coefficient by the use of a feedback signal whose high-frequency components are removed is proposed. However, if components in a part of frequency bands are simply removed in order to limit a bandwidth, distortion included in the part of the frequency bands is not taken into consideration. Accordingly, there is room for improvement in the accuracy of compensation coefficient learning in the above learning method.